In any year, 10 percent of Medicare beneficiaries account for 70 percent of expenditures. If these high utilizers can be identified accurately early on, they can be targeted for special services in an attempt to prevent the utilization of more expensive services. The proposed research will develop an economical and efficient means of identifying older persons who will subsequently incur high health care costs. To do so, we will conduct a secondary analysis of the 3 sites of the Established Populations for Epidemiologic Studies for Epidemiologic Studies of the Elderly (EPESE), conducted from 1980-1992. Using self-report, physical examination, and inexpensive laboratory data obtained in 1988, we will develop prediction rules for 1-year and 4-year Medicare Part A health care utilization. We will use a two-stage approach, the first of which relies on self-report information that could be obtained by mail, telephone, or eventually internet (or in some cases taken from administrative data) and the second of which would need to be performed in-person by a trained assistant with little or no medical training. We will also develop an efficient strategy for this risk identification that begins with self-report data and then adds physical examination and laboratory data only in cases when self-report cannot accurately classify predicted subsequent utilization. The accuracy of these prediction rules will also be examined in subjects who have different patterns of prior health care utilization.